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Full-Text Articles in Physical Sciences and Mathematics
Large-Scale Discovery Of Visual Features For Object Recognition, Drew Linsley, Sven Eberhardt, Dan Shiebler, Thomas Serre
Large-Scale Discovery Of Visual Features For Object Recognition, Drew Linsley, Sven Eberhardt, Dan Shiebler, Thomas Serre
MODVIS Workshop
A central goal in vision science is to identify features that are important for object and scene recognition. Reverse correlation methods have been used to uncover features important for recognizing faces and other stimuli with low intra-class variability. However, these methods are less successful when applied to natural scenes with variability in their appearance.
To rectify this, we developed Clicktionary, a web-based game for identifying features for recognizing real-world objects. Pairs of participants play together in different roles to identify objects: A “teacher” reveals image regions diagnostic of the object’s category while a “student” tries to recognize the object. Aggregating …
Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker
Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker
MODVIS Workshop
Visual attention models can explain a rich set of physiological data (Reynolds & Heeger, 2009, Neuron), but can rarely link these findings to real-world tasks. Here, we would like to narrow this gap with a novel, physiologically grounded model of visual attention by demonstrating its objects recognition abilities in noisy scenes.
To base the model on physiological data, we used a recently developed microcircuit model of visual attention (Beuth & Hamker, in revision, Vision Res) which explains a large set of attention experiments, e.g. biased competition, modulation of contrast response functions, tuning curves, and surround suppression. Objects are represented by …